1 What is known of Arctic kelps?

1.1 Present

  • Evidence suggests that many Arctic coasts should support seaweed
  • In Canada, kelp has been reported and documented along Arctic and subarctic coastlines
  • However, baseline measures of the extent of kelp communities are missing in much of the region

1.2 Future

  • Rapid environmental changes such as declining sea ice, increased ocean temperatures and freshwater inputs are occurring along these coasts
  • Research suggests northern expansion of kelp forests with climate change
  • Therefore the relationships between environmental factors and the presence of kelp forests in the Canadian arctic are critical to understand

2 ArcticKelp project

  • Where are kelp in the Arctic and what drives their distribution?
  • The Arctic is changing quickly so we should figure this out ASAP
  • Kelp abundance records (percent cover by species) were obtained from ArcticKelp project
  • This dive research conducted throughout the Canadian Arctic in 2014 - 2019
    • 5 - 20 m photograph quadrats
  • Do these drivers differ for different functional groups?
    • Total kelp cover
    • Laminariales (Laminaria sp. + Sacharina sp.)
    • Agarum
    • Alaria

2.1 Campaigns

2.2 Mean cover

3 Environmental conditions

3.1 Abiotic data

  • NAPA (3-Oceans) model
    • Model outputs supplied by the Bedford Institute of Oceanography (BIO)

    • Based on the NEMO community ocean model

      (Madec and others, 2015)
    • Ice from the LIM3 model

      (Rousset et al., 2015; Vancoppenolle et al., 2009)
    • Daily surface resolution: 1998 to 2015
    • Five day (pentad) resolution at 75 depth layers
    • Tri-polar grid
      • 10 to 20 km resolution

3.2 Biotic data

  • Bio-ORACLE
    • 18 total geophysical, biotic, and environmental variables
    • Collection from many different datasets
    • Surface and benthic coverage
    • Data from 2000 - 2014 for most
    • Single values per pixel; min, mean, max, and range for most
    • 5 arcdegree spatial resolution (~9.2 km at the equator)

(Assis et al., 2018; Tyberghein et al., 2012)

4 Modelling distribution

  • Using existing models, can we predict the % coverage of kelp?
  • Which variables are important?
  • What is the accuracy of the model?
  • What is the range in accuracy?
  • What is the distribution of inaccuracy?

4.1 Methods

  • Highly correlated variables were removed
  • A random forest model was used
  • After many iterations the best variables were found
  • These best variables were used over many iterations again to find the best models

4.2 Variables

4.2.1 Total kelp

Data layer Units MSE change
Sea water temperature (mean at min depth) °C 92
Dissolved oxygen concentration (mean at min depth) mol/m 85
Ice divergence 1e-8s-1 79
Sea ice thickness (mean) m 72
solar heat flux transmitted through ice: sum over categories W/m2 69
Ice fraction 1 69
Ice concentration for categories % 68
Depth m 68
wind stress module N/m2 66
Iron concentration (mean at min depth) mol/m 63

4.2.2 Laminariales

Data layer Units MSE change
Depth m 48
Latitude degree 47
Longitude degree 32
Photosynthetically available radiation (mean) Einstein/m/day 25
brine salt flux 0.001*kg/m2/day 16
Sea ice thickness (mean) m 15
Sea Water Salinity 0.001 14
Sea Surface Salinity 0.001 14
Sea ice thickness (range) m 14
Sea ice concentration (mean) fraction 14

4.2.3 Agarum

Data layer Units MSE change
Ice thickness (cell average) m 68
Light at bottom (mean at min depth) mol/m/s 54
Iron concentration (mean at min depth) mol/m 48
Primary production (mean at min depth) g/m/day 46
Chlorophyll concentration (mean at min depth) mg/m 43
Carbon phytoplankton biomass (mean at min depth) mol/m 42
Ice velocity along i-axis at I-point (ice presence average) m/s 41
Depth m 33
Current velocity (mean at min depth) m/s 33
Nitrate concentration (mean at min depth) mol/m 31

4.2.4 Alaria

Data layer Units MSE change
Depth m 26
total flux at ocean surface W/m2 10
non-solar heat flux at ocean surface W/m2 9
Sea Water Salinity 0.001 8
Sea Surface Salinity 0.001 8
sea surface height m 8
non solar Downward Heat Flux W/m2 7
Nitrate concentration (mean at min depth) mol/m 5
Sea water temperature (mean at min depth) °C 5
Sea ice thickness (mean) m 4

4.3 Confidence

4.3.1 Total cover

4.3.2 Laminariales

4.3.3 Agarum

4.3.4 Alaria

5 Results

  • Note that the colour scales are not the same between figures

5.1 Total cover

5.2 Laminariales

5.3 Agarum

5.4 Alaria

6 Further work

  • Better screening of variables used in model
  • Increase resolution of data

7 Acknowledgements

Dr. Youyu Lu and Dr. Xianmin Hu for NAPA model access

This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund, through the Ocean Frontier Institute.

References

Assis, J., Tyberghein, L., Bosch, S., Verbruggen, H., Serrão, E. A., and De Clerck, O. (2018). Bio-oracle v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography 27, 277–284.

Madec, G., and others (2015). NEMO ocean engine.

Rousset, C., Vancoppenolle, M., Madec, G., Fichefet, T., Flavoni, S., Barthélemy, A., et al. (2015). The louvain-la-neuve sea ice model lim3. 6: Global and regional capabilities.

Tyberghein, L., Verbruggen, H., Pauly, K., Troupin, C., Mineur, F., and De Clerck, O. (2012). Bio-oracle: A global environmental dataset for marine species distribution modelling. Global ecology and biogeography 21, 272–281.

Vancoppenolle, M., Fichefet, T., Goosse, H., Bouillon, S., Madec, G., and Maqueda, M. A. M. (2009). Simulating the mass balance and salinity of arctic and antarctic sea ice. 1. Model description and validation. Ocean Modelling 27, 33–53.